These are research projects that have been (mostly) dormant for a few years.

Descriptions of more recent projects appear here.

Real robots must effectively collect, interpret, and act upon sensor
data. How sophisticated must a robot's sensors be to complete a
given task? What are the neccessary conditions? We seek the
*simplest* robots that can complete a task, giving a precise
meaning to the idea of simpleness. My goal is to develop a clean,
formal technique for comparing robot systems and for studying their
ability to complete tasks of varying difficulty. This work draws
inspiration from the theory of computation, which plays a similar
role in the core of computer science.

Localization, the task of determining a robot's position within its
environment, is one of the most important problems for mobile robots. How hard
is this problem, in terms of the sensing and motion ability needed to complete
it? This work is an investigation of the information requirements of the
localization task. We found upper and lower bounds on the sensing and motion
capabilities needed for localization and implemented our algorithms on Roomba
vacuum cleaner robots.
## Pareto Optimal Coordination

In many situations, teams of robots must interact in a shared workspace. If the robots have distinct goals and objective functions, then the design of collision-free coordination plans for these teams is a multi-objective optimization problem. This work uses the idea of*Pareto optimality* to generate a set of
non-dominated solutions to multiple-robot coordination problems.

In many situations, teams of robots must interact in a shared workspace. If the robots have distinct goals and objective functions, then the design of collision-free coordination plans for these teams is a multi-objective optimization problem. This work uses the idea of